Triple

T6845334
Position Surface form Disambiguated ID Type / Status
Subject Sabine Mountains E157879 entity
Predicate historicalRegion P915 FINISHED
Object Sabina E203655 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Sabina | Statement: [Sabine Mountains, historicalRegion, Sabina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sabina
Context triple: [Sabine Mountains, historicalRegion, Sabina]
  • A. Sabina chosen
    Sabina is a historical region of central Italy, traditionally inhabited by the Sabines and known for its rugged landscape and proximity to ancient Rome.
  • B. Sabina
    Sabina is a central character in Thornton Wilder’s play "The Skin of Our Teeth," serving as both a maid and a self-aware, often comedic commentator who breaks the fourth wall to reflect on the absurdities of human existence.
  • C. Corina
    Corina is a feminine given name used in various cultures, often considered a variant of names like Corine or Corinna.
  • D. Romina
    Romina is an Italian-American actress and singer best known as half of the pop duo Al Bano & Romina Power.
  • E. Luciana
    Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c6882ed4c081909dc465a7cf8838be completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d7ca96008190ba79563c2a9a9b0e completed March 27, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72fc42e688190baa8413883e5506c completed March 28, 2026, 1:32 a.m.
Created at: March 27, 2026, 2:19 p.m.